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Big Data
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Big Data and Business Strategy

Big Data and Business Strategy

The analysis of the Big Data provides valuable information on key elements such as markets or business directions, identifying which ones will potentially generate the highest profits. It is fundamental for making strategic decisions such as expansion and development plans or financial analysis. It has therefore become an indispensable source for the industrial sector in two main aspects:


Hyperconnected context
A very high and growing percentage of business activities go through or are related to the Internet. This increases the amount of data recorded and stored by companies, both online and offline, to exponential levels, making it challenging and difficult for businesses to manage and analyse this data. While industrial companies years ago lived exclusively in limited geographical areas and had a constant and highly localised demand, they now have to live and coexist with many other companies in a context where physical barriers do not exist. In this new context, information is power, but only if it is used correctly.


If a company chooses not to implement Big Data, it will be left behind and will lose any competitive advantage in favor of its competitors, destined not to survive. If a company chooses to implement Big Data in a complementary way and without a strategy, it will have spent time and money to end up like the first one. But if a company manages to internalise its Big Data strategy and connect its processes, it will have infinitely more possibilities of success in the 4.0 environment.


Smart Factories 

Big Data helps to integrate previously isolated systems so that companies can obtain a complete visualisation of the manufacturing processes. In addition, it automates data collection and analysis, facilitating a better understanding of the status of each system, both together and separately.


The applicability of Big Data also lies in the business strategies directly involved in manufacturing, resulting in systems such as:

  • Enterprise Resource Planning
  • Supplier Relationship Management Systems
  • Product Life Cycle Management Systems
  • More Environmentally Responsible Systems


The information is analysed in three layers of perspectives that include data from the past, present and future, which allows for a complete view that includes reasoning on causalities and projections into the future. This data-based, integrated supply chain management approach, while increasing value and efficiency in the manufacturing process, helps reduce inventory and capital requirements in the medium to long term.


What would Industry 4.0 be without Big Data?
Modern factories are becoming increasingly complex and interconnected, creating new challenges that automation, driven by Big Data, can address. The large amounts of data resulting from the IoT and modern computer systems have enabled intelligent factories to quickly boost their efficiency and make significant gains in terms of increased uptime, accelerated production and reduced errors.


The possibilities of interconnection, facilitated by the IoT, have been creating very large and complex information networks. Without the Big Data, 4.0 technologies would not have been able to decipher and extract value from all that information in order to learn, generate predictive analysis patterns and operate autonomously and in such a precise manner. Therefore, without Big Data, there would have been no 4.0 industry, nor the intelligent technologies that support it.


We help you structure your data
The Nexus Integra integrated operations platform and its advanced technology system allows you to apply Big Data and AI in an industrial environment. The platform will guide you through the entire process from data acquisition to data exploitation, offering you a structured Big Data platform that makes it easy for data scientists to apply technologies such as AI and Machine Learning in line with your company’s strategy.

Nexus Integra as an integral operations center and Big Data platform allows you to extract all the value from the data.


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